Graph extract example

Import:



In [1]:

    
%matplotlib inline

from graph_extract import Graph

Define properties of your graph:



In [2]:

    
path = 'graph_1.png'
x = (1500, 900)
y = (75, -100)

Make the graph object:



In [3]:

    
g = Graph('graph_1.png', xlim=x, ylim=y)

The image name is used as the name:



In [4]:

    
g.name









    Out[4]:





'graph_1'

Can visualize the image:



In [5]:

    
g.show_img()









    Out[5]:





<matplotlib.image.AxesImage at 0x117e2f588>

The fit is obtained as a series from the data property of the Graph object:



In [6]:

    
g.data.head()









    Out[6]:





1500.000000   -4.631295
1499.598125   -4.316547
1499.196249   -4.316547
1498.794374   -4.316547
1498.392498   -4.316547
Name: graph_1, dtype: float64

This can be visualized:



In [7]:

    
g.show_data()









    Out[7]:





<matplotlib.axes._subplots.AxesSubplot at 0x112e1f588>

This can be superimposed over the original image:



In [8]:

    
plt.figure(figsize=(10,8))
plt.axis('off')
g.show_fit()

We can save out the data using pandas' to_csv method:



In [9]:

    
g.data.to_csv('graph_1.csv')